Mauricio D.
Data Scientist

Skills

Spark

Sql

Databricks

Python

Microsoft Azure

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Bio

Data Scientist and Machine Learning Engineer with a robust foundation in mathematics, statistics, and programming. Specializes in addressing business challenges through data analysis and machine learning techniques. Employs a proactive and meticulous approach to ensure safe and effective deployment of models, yielding valuable insights to enhance processes, increase efficiency, and drive business growth. Maintains up-to-date knowledge of industry trends and advancements through continuous learning via courses and literature. Committed to becoming a leading expert in Machine Learning, Artificial Intelligence, and Blockchain, with a vision to foster positive global impact.

Machine Learning Engineer
11/1/2023 - Present

Architected and led end-to-end machine learning solutions using Python, PySpark, MLflow, and major ML libraries. Developed, monitored, and implemented models on cloud platforms such as Databricks and Azure ML. Provided code reviews and guidance for junior team members, promoting a culture of continuous learning and innovation in machine learning practices.
Data Scientist
2/1/2022 - 11/1/2023

The role in the Pricing Data Science team entailed generating data science solutions to optimize pricing strategies. Developed proficiency in Python and PySpark to implement unsupervised outlier detection models for assessing unbilled orders with irregular patterns. Proficiency in pipeline orchestration was demonstrated using Kedro, while MLFlow was utilized for monitoring model performance. Enhanced skills in geospatial data analysis to extract valuable insights and functionalities for machine learning models. The technical expertise extended to creating, tuning, and validating machine learning models using tools such as Scikit-Learn, Prophet, and MLFlow. Efficient development and maintenance of machine learning pipelines from ETL to performance visualization in production were achieved following MLOps best practices, leveraging Kedro, Python, PySpark, and Power BI. Acquired experience with cloud platforms including Azure Data Lake Store, Databricks, and Azure ML. Additionally, provided mentorship to interns and junior team members in machine learning, with contributions such as detailed notebooks available on GitHub in the Machine_Learning_Algorithms repository.
Data Science Intern
2/1/2021 - 2/1/2022

Developed and implemented geoprocessing solutions using Python and created interactive dashboards with Power BI to automate the detection of competing fuel stations, significantly assisting in business decision-making. Successfully piloted this project with an 81% acceptance rate by the tactical team, which continues to support the company's pricing policy. Developed a churn prediction model utilizing Python, Scikit-Learn, XGBoost, and MLflow, achieving an AUC Score of approximately 0.80 ± 0.03 in backtest validation. The project is in the pilot phase, with the tactical team currently testing predictions and employing statistical tests for efficacy validation. Earned the recognition of Universo Explorer in 2021 due to commitment to continual learning through the company's internal training platform.